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BERT (Czech Wikipedia)

Analysis of information sources in references of the Wikipedia article "BERT" in Czech language version.

refsWebsite
Global rank Czech rank
3googleblog.com
1,272nd place
5,345th place
3arxiv.org
69th place
196th place
1towardsdatascience.com
8,920th place
7,263rd place
1invgate.com
low place
low place
1ibm.com
1,131st place
1,165th place
1vitalflux.com
low place
low place
1blog.google
2,218th place
9,180th place
1web.archive.org
1st place
1st place
1techscience.com
low place
low place
1worldcat.org
5th place
3rd place
1doi.org
2nd place
4th place
1h2o.ai
low place
low place

arxiv.org (Global: 69th place; Czech: 196th place)

  • DEVLIN, Jacob; CHANG, Ming-Wei; LEE, Kenton. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv:1810.04805 [cs]. 2019-05-24. ArXiv: 1810.04805 version: 2. Dostupné online [cit. 2022-10-27]. 
  • ROGERS, Anna; KOVALEVA, Olga; RUMSHISKY, Anna. A Primer in BERTology: What we know about how BERT works. arXiv:2002.12327 [cs]. 2020-11-09. ArXiv: 2002.12327. Dostupné online [cit. 2022-10-27]. 
  • ZHU, Yukun; KIROS, Ryan; ZEMEL, Richard. Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books. arXiv:1506.06724 [cs]. 2015-06-22. ArXiv: 1506.06724. Dostupné online [cit. 2022-10-27]. 

blog.google (Global: 2,218th place; Czech: 9,180th place)

  • Understanding searches better than ever before. Google [online]. 2019-10-25 [cit. 2023-08-19]. Dostupné online. (anglicky) 

doi.org (Global: 2nd place; Czech: 4th place)

  • ABAS, Ahmed; ELHENAWY, Ibrahim; ZIDAN, Mahinda. BERT-CNN: A Deep Learning Model for Detecting Emotions from Text. Computers, Materials & Continua. 2021, roč. 71, čís. 2, s. 2943–2961. Dostupné online [cit. 2023-08-19]. ISSN 1546-2218. doi:10.32604/cmc.2022.021671. (anglicky) 

googleblog.com (Global: 1,272nd place; Czech: 5,345th place)

ai.googleblog.com

  • Transformer: A Novel Neural Network Architecture for Language Understanding. ai.googleblog.com [online]. 2017-08-31 [cit. 2023-08-20]. Dostupné online. (anglicky) 
  • Open Sourcing BERT: State-of-the-Art Pre-training for Natural Language Processing. ai.googleblog.com [online]. [cit. 2022-10-27]. Dostupné online. (anglicky) 
  • Open Sourcing BERT: State-of-the-Art Pre-training for Natural Language Processing. ai.googleblog.com [online]. 2018-11-02 [cit. 2023-08-20]. Dostupné online. (anglicky) 

h2o.ai (Global: low place; Czech: low place)

  • BERT Basics: What It Is, Creation, and Uses in AI. h2o.ai [online]. [cit. 2022-10-27]. Dostupné online. 

ibm.com (Global: 1,131st place; Czech: 1,165th place)

  • AJAYI, Demi. How BERT and GPT models change the game for NLP [online]. 2020-12-03 [cit. 2023-08-19]. Dostupné online. (anglicky) 

invgate.com (Global: low place; Czech: low place)

blog.invgate.com

  • MOTTESI, Celeste. GPT-3 vs. BERT: Comparing the Two Most Popular Language Models. blog.invgate.com [online]. [cit. 2023-08-19]. Dostupné online. (anglicky) 

techscience.com (Global: low place; Czech: low place)

  • ABAS, Ahmed; ELHENAWY, Ibrahim; ZIDAN, Mahinda. BERT-CNN: A Deep Learning Model for Detecting Emotions from Text. Computers, Materials & Continua. 2021, roč. 71, čís. 2, s. 2943–2961. Dostupné online [cit. 2023-08-19]. ISSN 1546-2218. doi:10.32604/cmc.2022.021671. (anglicky) 

towardsdatascience.com (Global: 8,920th place; Czech: 7,263rd place)

  • HOREV, Rani. BERT Explained: State of the art language model for NLP. Medium [online]. 2018-11-17 [cit. 2023-08-19]. Dostupné online. (anglicky) 

vitalflux.com (Global: low place; Czech: low place)

  • KUMAR, Ajitesh. BERT vs GPT Models: Differences, Examples [online]. 2023-08-19 [cit. 2023-08-20]. Dostupné online. (anglicky) 

web.archive.org (Global: 1st place; Czech: 1st place)

worldcat.org (Global: 5th place; Czech: 3rd place)

  • ABAS, Ahmed; ELHENAWY, Ibrahim; ZIDAN, Mahinda. BERT-CNN: A Deep Learning Model for Detecting Emotions from Text. Computers, Materials & Continua. 2021, roč. 71, čís. 2, s. 2943–2961. Dostupné online [cit. 2023-08-19]. ISSN 1546-2218. doi:10.32604/cmc.2022.021671. (anglicky)